A communications concept could pinpoint a person infected with a deadly, contagious virus in the middle of a crowded airport.
Pyramidal graphs resulting from statistical analyses of EEG recordings can improve our understanding of epileptic seizures.
Insyab, a technology startup specializing in smart solutions allowing robots and drones to collaborate on the execution of common tasks, resulted from three years of its founders' dedicated research at KAUST.
Exploring the links between natural climate cycles and the sea-surface temperature of the Red Sea reveals a cooling trend during the next few decades.
Powerful computer simulations are revealing new insights into water exchanges between the Red Sea and the Gulf of Aden.
A remote sensing algorithm offers better predictions of Red Sea coral bleaching and can be fine tuned for use in other tropical marine ecosystems.
Algal blooms in the Red Sea can be detected with a new method that accounts for dust storms and aerosols.
A recent study by a team including KAUST Earth scientists and oceanographers revealed that surface temperatures in the Red Sea may be cooling rather than rising.
Automatic detection of uncharacteristic data sequences could change the way data is processed and analyzed.
Modeling the 3D structure of Red Sea eddies shows how transport of energy and biochemical materials influences circulation patterns in the Red Sea.
Study of the mismatch between spatial environmental data and a commonly used statistical analysis suggests simpler statistics are sufficient in many cases.
KAUST alumna Yuan Yan recently received an honorable mention from the American Statistical Association (ASA) for her paper entitled "Vector Autoregressive Models with Spatially Structured Coefficients for Time Series on a Spatial Grid." Yan, who participated in the ASA student paper competition last year, will be officially recognized for her contribution later this year at the association's 2019 Joint Statistical Meetings in Denver, Colorado, U.S., from July 27 to August 1.
KAUST Ph.D. statistics student Jian Cao was recently selected as a best paper award winner by the American Statistical Association (ASA) for his paper entitled "Computing High-Dimensional Normal and Student-t Probabilities with Tile-Low-Rank Quasi-Monte Carlo and Block Reordering." Cao's paper was chosen in an ASA student paper competition under the section on Statistical Computing.
A tiny, portable radar device could allow visually impaired people, or unmanned moving devices, to detect objects in real time.
The latest statistical methods from research on complex high-dimensional environmental data also yield powerful tools for interpreting brain activity.